While tourism is influenced by a number of factors, these factors actually influence the revenues accruing to the given tourist destination country. In order to ensure that a country gets the optimal income from tourism, it is important for the specific tourist destination to know the relationship that exists between and among the various factors in the industry.
Given that tourists come from diverse places, the mode being informed or getting knowledge of a particular tourist attraction is unlikely to be the same; or at least the mode is related to the place of origin of the tourist. This is notwithstanding the differentials in development from place to place (implying that the same mode of advertisement is least likely to be formality for all the places of origin). Since promoting a tourist destination to interested tourists will lead to a number of questions, an evaluation of the underpinning factors will help in carrying out the exercise beneficially. For instance, what mode of advertisement should the tourist destination use for UK originating tourists? What kind of recreation facilities do we put in place to attract them? Do they bother about recreational facilities at all? Is there relationship between the number of adult tourists and their total spending? So should we or should we not advertise for package tourism? These are among the key questions that if answered they may boost the process of decision making.
In the following analysis, an evaluation of the above factors is carried out based on data collected by Sabah Tourism Board in 2007. The main objective of collecting and evaluating the data is to assess the relationship, if any, that exists between and among various factors that relate to each other to cause an influence on the origin of tourists attracted to the Sabah Tourist centre.
Findings and Discussion
TASK 1 (10 marks)
Organise the data obtained from the survey and present it using appropriate charts or graphs.
The graph gives a clear picture of how the mean total spending for the four nationalities is varied with Japan scoring the highest, followed by the UK, South Korea and Taiwan in that order.
The highest number of adults is registered in Japan, followed by Taiwan and UK which tie and S. Korea comes last with 8 adults. However, looking at the following table and the chart that follow it, which show the relationship between total spending and the mean number of adults for each nationality, a clearer picture of the relationship existing between the two variables can be drawn out.
In the chart 3 above, the parameters are the total numbers of adults, total number of days of holiday and the mean spending. The chart indicates that though South Korea’s are fewest, they spend longest number of days for their holidays. Their mean spending is however lower than that of UK despite the fact that the UK tourists spend almost as equal the number of days as the number of tourists.
In terms of the number of days, Japan still has the highest scoring 10 days followed, in order, by S. Korea having 9 days then Taiwan and UK tying with 8 days.
TASK 2 (22 marks)
(a) Find the mean and standard deviation of the spending per group for each nationality.
Japan has the highest standard deviation of $325.00792 and it still exhibits the highest mean of $1,000.2500 in total spending. It is followed by the UK which has a mean of $954.7200 and standard deviation of $287.01209. Taiwan has the lowest statistics among the group in terms of total spending and it has $741.6900 of mean with a standard deviation of $287.01209. This implies that on average, the total spending among the Japanese is higher than the other groups while that of Taiwan is the lowest. The graph labeled figure 4 can give a clear picture of the means and std. Deviations for each nationality.
(b) Use the hypothesis test to assess whether these means are different. Show the standard error, confidence interval and p-value for each comparison.
|Paired Samples Statistics- Table 3|
|Nationality||Mean||N||Std. Deviation||Std. Error Mean|
|South Korea||Pair 1||Total spending||$789.3600||100||$244.01252||$24.40125|
|Taiwan||Pair 1||Total spending||$741.6900||100||$241.21007||$24.12101|
|Japan||Pair 1||Total spending||$1,000.2500||100||$325.00792||$32.50079|
|UK||Pair 1||Total spending||$954.7200||100||$287.01209||$28.70121|
According to the output results in the table 2 above, the Standard Errors for S. Korea, Taiwan, Japan and UK are $24.40125, $24.12101, $32.50079 and $28.70121 respectively. The confidence interval for all the nationalities is 95% while the p- values are approximately 0.000 in each nationality.
TASK 3 (21 marks)
(a) Use chi-square analysis to determine whether there is any relationship between the overall level of satisfaction of the holiday and the nationality.
With 9 degrees of freedom and p- value of approximately 0.000, the chi-square value is 146.117 and therefore the relationship between nationality and satisfaction strong.
(b) Use the hypothesis test to assess whether these means are different. Show the standard error, confidence interval and p-value for each comparison.
Ho: There is no difference in the means (Mean difference = 0)
Ha: There is a difference in the means (Mean difference ≠ 0)
From the results we can see that there is significance in the results at p-value less than our significance value of 0.05. This implies that for all the four cases (nationalities), the difference in means is actually significant and it supports rejection of our null hypothesis (Hinton 1997).
(c) Use chi-square analysis to determine whether there is any relationship between how they hear about the tourist destination and the nationality.
In order to carry out a chi-square test to test the relationship between advertisement and nationality, it was important to do a cross tabulation of the two variables given that they have cases and hence forms the contingency table 7 shown above (Bruin 20006). The results of the chi-square test indicate a strong relationship between nationality and the mode of advertisement used.
TASK 4 (12 marks)
(a) For each nationality, find a multiple linear regression equation for the group spending on the number of days stayed and the number of adults.
- South Korea
Spending = 99.869 No of days + 96.820 No. of Adults + 87.564
Spending = 99.520 No. of days + 115.120 No. of Adults + 19.135
Spending = 135.000 No. of days + 129.470 No. of Adults + 4.217
(b) Find the coefficients of correlation and determination for each of the above regression equations.
- South Korea: coefficient of correlation= 0.926: coefficient of determination= 0.857
- Taiwan: coefficient of correlation= 0.909; coefficient of determination= 0.827
- Japan: coefficient of correlation= 0.917; coefficient of determination= 0.841
- UK: coefficient of correlation= 0.915; coefficient of determination= 0.836
Looking at the regression and relating it to chart 3, we can see the reason why the coefficients for Japan for number of days and adults are higher than other nationalities. This as can be seen from the spending column of the chart, the Japanese tourists spend more during their holidays as compared to the other tourists despite the fact that the mean number of days for UK is even greater than that of Japan. Even the mean number of adults for UK is also greater than the one for Japan. However, it must be noted that if the number of days and the number of adults is held constant, Japanese tourists are likely to generate the least revenue from tourist spending. Thus, more advertisement to Japanese must be bolstered to ensure that the number of tourists from Japan and the number of days they spend increase.
The mode of advertisement is also found to be strongly related to the origin of the tourist in that tourists from a particular place will be better reached by specific modes of advertising. This agrees with the findings of Beerli et al (2003) who contend that because of difference in cultural aspects among other factors, tourist attraction in terms of country of origin is highly related to mode of advertising set to attract them (Beerli, Josefa and Martin 2003).
Bruin, J. newtest: command to compute new test. UCLA: Academic Technology Services, Statistical Consulting Group; 2006 http://www.ats.ucla.edu/stat/stata/ado/analysis/.
Introduction to SAS. UCLA: Academic Technology Services, Statistical Consulting Group; 2006. from http://www.ats.ucla.edu/stat/sas/notes2/ (accessed August 11, 2009).
Hinton, R. P. Statistical Guide for Social Science Students. NY (USA); Rutledge: 1997
Beerli, C., A., Josefa, J. D. and D. Martín “Tourists’ characteristics and the perceived image of tourist destinations: a quantitative analysis—a case study of Lanzarote, Spain” Tourism Management 25(5), 2004: 623-636.
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